{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Coding with Qiskit Episode 8\n",
    "\n",
    "# Noise and Measurement Error Mitigation\n",
    "\n",
    "#### Written by Abraham Asfaw, IBM TJ Watson Research Center"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this episode of Coding with Qiskit, we learned about noise, and saw how it affects quantum computation on real devices by introducing errors.\n",
    "\n",
    "To learn more about measurement error mitigation, check out [the section in our open-source Qiskit textbook on this topic](https://community.qiskit.org/textbook/ch-quantum-hardware/measurement-error-mitigation.html).\n",
    "\n",
    "**Link to Episode 8:** https://youtu.be/yuDxHJOKsVA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"960.0\"\n",
       "            height=\"540.0\"\n",
       "            src=\"http://www.youtube.com/embed/yuDxHJOKsVA\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1120ee0f0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "IFrame(src=\"http://www.youtube.com/embed/yuDxHJOKsVA\", width=1920/2, height=1080/2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Building a simple quantum circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qiskit.circuit.instructionset.InstructionSet at 0x13926fcc0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nqubits = 3\n",
    "circuit = QuantumCircuit(nqubits, nqubits)\n",
    "circuit.h(0)\n",
    "circuit.cx(0,1)\n",
    "circuit.cx(1,2)\n",
    "circuit.measure([0,1,2], [0,1,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 517.72x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulating the quantum circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "simulator = Aer.get_backend('qasm_simulator')\n",
    "sim_result = execute(circuit, backend=simulator, shots=1024).result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.visualization import plot_histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(sim_result.get_counts(circuit))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Running the quantum circuit on a real quantum computer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "IBMQ.load_account()\n",
    "provider = IBMQ.get_provider(hub='ibm-q')\n",
    "device = provider.get_backend('ibmqx2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "job = execute(circuit, backend=device, shots=1024)\n",
    "#print(job.job_id())\n",
    "from qiskit.tools.monitor import job_monitor\n",
    "job_monitor(job)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_result = job.result()\n",
    "plot_histogram(device_result.get_counts(circuit))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibrating measurement errors using Qiskit Ignis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit.ignis.mitigation.measurement import (complete_meas_cal, CompleteMeasFitter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cal_circuits, state_labels = complete_meas_cal(qr=circuit.qregs[0], \n",
    "                                               circlabel='measurement_calibration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 457.52x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cal_circuits[7].draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cal_circuits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Job Status: job has successfully run\n"
     ]
    }
   ],
   "source": [
    "cal_job = execute(cal_circuits,\n",
    "             backend=device,\n",
    "             shots=8192,\n",
    "             optimization_level=0)\n",
    "#print(cal_job.job_id())\n",
    "job_monitor(cal_job)\n",
    "cal_results = cal_job.result()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(cal_results.get_counts(cal_circuits[3]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating the Measurement Fitter Object in Ignis "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "meas_fitter = CompleteMeasFitter(cal_results, state_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "meas_fitter.plot_calibration()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "meas_filter = meas_fitter.filter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mitigating the measurement errors in our previous device run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "mitigated_result = meas_filter.apply(device_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_counts = device_result.get_counts(circuit)\n",
    "mitigated_counts = mitigated_result.get_counts(circuit)\n",
    "plot_histogram([device_counts, mitigated_counts], \n",
    "               legend=['device, noisy', 'device, mitigated'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Running error mitigation on a second circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 517.72x264.88 with 1 Axes>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "circuit2 = QuantumCircuit(3,3)\n",
    "circuit2.x(1)\n",
    "circuit2.h(0)\n",
    "circuit2.cx(0,1)\n",
    "circuit2.cx(1,2)\n",
    "circuit2.measure([0,1,2], [0,1,2])\n",
    "circuit2.draw(output='mpl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(\n",
    "    execute(circuit2, backend=simulator, shots=1024).result().get_counts(circuit2)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "device_counts_2 = execute(circuit2, backend=device, shots=1024).result().get_counts(circuit2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram(device_counts_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "mitigated_counts_2 = meas_filter.apply(device_counts_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_histogram([device_counts_2, mitigated_counts_2], legend=['device, noisy','device, mitigated'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Tutorials\n",
    "For detailed information about Qiskit, check out the tutorials in the Github repository:\n",
    "\n",
    "https://github.com/Qiskit/qiskit-iqx-tutorials\n",
    "\n",
    "For a pedagogical presentation of the mathematics behind the Bernstein-Vazirani algorithm, check out our open-source `Learn Quantum Computation using Qiskit` textbook:\n",
    "\n",
    "https://community.qiskit.org/textbook/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Version"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's good to note the Qiskit version that was used in your work. One way to do this is print the version at the bottom of the Jupyter notebook using"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'qiskit-terra': '0.9.0',\n",
       " 'qiskit-ignis': '0.2.0',\n",
       " 'qiskit-aqua': '0.6.0',\n",
       " 'qiskit': '0.12.0',\n",
       " 'qiskit-aer': '0.3.0',\n",
       " 'qiskit-ibmq-provider': '0.3.2'}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import qiskit\n",
    "qiskit.__qiskit_version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style='width: 100%; background-color:#d5d9e0;padding-left: 10px; padding-bottom: 10px; padding-right: 10px; padding-top: 5px'><h3>This code is a part of Qiskit</h3><p>&copy; Copyright IBM 2017, 2019.</p><p>This code is licensed under the Apache License, Version 2.0. You may<br>obtain a copy of this license in the LICENSE.txt file in the root directory<br> of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.<p>Any modifications or derivative works of this code must retain this<br>copyright notice, and modified files need to carry a notice indicating<br>that they have been altered from the originals.</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import qiskit.tools.jupyter\n",
    "%qiskit_copyright"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "qiskitdevl",
   "language": "python",
   "name": "qiskitdevl"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
